Concepedia

Textual Origin Detection

Textual Origin Detection is a computational methodology within source provenance analysis that identifies the ultimate source or origin of a given text by distinguishing linguistic, structural, or metadata-based markers unique to its provenance, thereby differentiating it from other text attribution tasks.

2

Publications

132

Citations

7

Authors

5

Institutions

Publications per year

2017–2026

0

Parents

Publications

2

1–2 of 2

Authors

7

  1. KP
    Kai Pan

    Xiangtan University, China

    1 publications · 91 citations

    1

    h-index

  2. BB
    Behshad Behzadi

    Laboratoire d'Informatique de l'École Polytechnique, France

    1 publications · 41 citations

    1

    h-index

  3. EJ
    E. James Whitehead

    University of California, Santa Cruz, United States

    1 publications · 91 citations

    1

    h-index

  4. OA
    Ossama Abdel Hamid

    Google (United States), United States

    1 publications · 41 citations

    1

    h-index

  5. SK
    Sunghun Kim

    Hong Kong University of Science and Technology, Hong Kong SAR China

    1 publications · 91 citations

    1

    h-index

1–5 of 7

Institutions

5

  1. University of California, Santa Cruz

    Santa Cruz, United States

    1 h-index

    3 publications

    273 citations

  2. Cairo University

    Giza, Egypt

    1 h-index

    1 publications

    41 citations

  3. École Polytechnique Fédérale de Lausanne

    Lausanne, Switzerland

    1 h-index

    1 publications

    41 citations

  4. Google (United States)

    Mountain View, United States

    1 h-index

    3 publications

    123 citations

  5. Google (Switzerland)

    Zurich, Switzerland

    1 h-index

    3 publications

    123 citations

1–5 of 5